Eur. Phys. J. Spec. Top. (2022) 231: 3275-3280
https://doi.org/10.1140/epjs/s11734-022-00724-1
https://doi.org/10.1140/epjs/s11734-022-00724-1
Editorial
Dynamics of the COVID-19 pandemic: nonlinear approaches on the modelling, prediction and control
Department of Mathematical Sciences, Politecnico di Torino, Turin, Italy
This special issue contains 35 regular articles on the analysis and dynamics of COVID-19 with several applications. Some analyses are on the construction of mathematical models representing the dynamics of COVID-19, and some are on the estimations and predictions of the disease, a few with possible applications. The various contributions report important, timely, and promising results, such as the effects of several waves, deep learning-based COVID-19 classifications, and multivariate time series with applications.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022
